Immunotherapy has reshaped modern medicine, especially in oncology, yet uneven patient responses, treatment resistance, and immune-related toxicities still limit its impact. This chapter focuses on synthetic immunomodulators, engineered agents that steer immune activity with tighter control than broad immunosuppressants or many first-generation biologics. We first revisited why classical immunomodulation was often blunt and toxic, and how advances in chemistry, synthetic biology, and nanotechnology now enable more selective immune tuning. We then organized the field into practical classes such as small molecules, synthetic peptides and peptidomimetics, cytokine mimetics, nucleic acid-based modulators, and synthetic checkpoint modulators, and explained how each can either strengthen protective immunity (for example, antitumor responses) or calm damaging inflammation in autoimmune and chronic inflammatory settings. We highlighted use cases that matter at the bedside, including vaccine adjuvants, reprogramming suppressive tumor microenvironments, sustaining cytotoxic and memory responses, and building rational combinations with chemotherapy, radiotherapy, and targeted therapy. Finally, we summarized the clinical direction and key translational bottlenecks, including delivery and biodistribution, toxicity ceilings from overactivation, and the need for biomarker-guided patient selection and sequencing. Overall, synthetic immunomodulators are moving the field from simply turning immunity up or down to tuning it with better timing, location, and cell-type precision. We concluded with practical markers that can track whether a strategy is working, including interferon response signatures, antigen-presenting cell activation, and early shifts in cytotoxic lymphocyte populations in patients over time.

ABSTRACT Background Ovarian cancer (OC) is a globally prevalent malignancy associated with a high mortality rate and marked biological heterogeneity, with most cases arising from epithelial cells and presenting as serous, endometrioid, or clear cell subtypes. Standard management is largely stage dependent and primarily involves cytoreductive surgery followed by platinum‐ and taxane‐based chemotherapy, with modifications based on disease extent and patient factors. Recent Findings In recent years, the therapeutic landscape of OC has evolved with the introduction of maintenance strategies and targeted therapies, particularly driven by advances in molecular profiling and the identification of biomarkers such as BRCA mutations and homologous recombination deficiency (HRD). These developments have led to the clinical integration of PARP inhibitors and anti‐angiogenic agents such as bevacizumab, which have improved disease control and survival outcomes as part of standard treatment strategies in OC, whereas immunotherapeutic approaches remain largely investigational and are currently limited to clinical settings. Metronomic chemotherapy (MCT), characterized by the continuous administration of low‐dose chemotherapeutic agents, has emerged as a promising alternative to conventional maximum tolerated dose regimens. MCT offers reduced systemic toxicity while exerting sustained antitumor effects through modulation of the tumor microenvironment, inhibition of angiogenesis, and enhancement of antitumor immune responses, thereby addressing key limitations of standard chemotherapy, including resistance and cumulative adverse effects. Furthermore, the integration of artificial intelligence (AI) into metronomic treatment strategies holds significant potential for optimizing drug selection, dosing schedules, and patient stratification. AI‐driven tools can facilitate predictive modeling, high‐throughput data analysis, and personalized treatment planning, ultimately enhancing therapeutic efficacy while minimizing toxicity. Conclusion This review summarizes current management strategies in OC with particular emphasis on maintenance therapies, targeted approaches, and emerging evidence supporting MCT and AI‐enabled approaches as potential future directions in OC therapy.

Pancreatic ductal adenocarcinoma (PDAC) remains among the deadliest malignancies, driven by its invasive nature and lack of effective biomarkers. Disruption of the epithelial barrier, mediated by tight junction components, is a critical yet underexplored contributor to PDAC progression. Claudins, integral regulators of tight junction integrity, display altered expression across cancers, but their prognostic and immunomodulatory roles in PDAC remain unclear. We performed an integrative analysis of 177 RNA-Seq datasets from TCGA and GTEx to characterize Claudin family alterations in PDAC. Differential expression, copy number variation, methylation, and co-expression networks were analyzed alongside clinical and survival data. Prognostic significance was assessed using Kaplan - Meier and Cox regression analyses, while immune cell infiltration was examined using deconvolution algorithms. Functional validation of Claudin-1 was conducted in Capan-1 cells using CRISPR/Cas9 knockout, followed by proliferation, wound-healing, and Western blot assays. Ten Claudin genes were significantly dysregulated, with Claudin-1 and Claudin-4 frequently amplified and associated with advanced stage and poor survival. High Claudin-1 expression correlated with reduced immune infiltration, indicating an immune-excluded phenotype characterized by immune cells retained in the tumor stroma but largely absent from the tumor parenchyma. Claudin-1 knockout markedly inhibited proliferation, migration, and EMT, evidenced by downregulation of Snail and Slug and restoration of E-cadherin expression. This integrative transcriptomic and functional study identifies Claudin-1 as a key driver of PDAC aggressiveness and immune modulation. These findings establish Claudin-1 as a promising prognostic biomarker and therapeutic target for restoring epithelial integrity and counteracting immune evasion in pancreatic cancer.

ABSTRACT Metastasis remains the leading cause of cancer‐related mortality and is increasingly recognized as a consequence of dynamic interactions between tumor cell plasticity and a heterogeneous tumor microenvironment (TME). Rather than being genetically fixed, cancer cells exhibit phenotypic flexibility, enabling reversible transitions among epithelial, mesenchymal, and stem‐like states in response to intrinsic programs and extrinsic microenvironmental cues, central to this adaptability. This review synthesizes emerging evidence that tumor progression is governed by reciprocal feedback loops between plastic tumor cells and distinct microenvironmental niches, including hypoxic cores, invasive margins, and perivascular regions. We highlight how stromal components, immune infiltrates, endothelial cells, and extracellular matrix (ECM) remodeling dynamically shape tumor cell states through biochemical and biophysical signals. Advances in single‐cell and spatial transcriptomic technologies have revealed the spatial organization and reversibility of these plastic phenotypes, uncovering rare but clinically significant drug‐tolerant persister populations. Importantly, we discuss plasticity‐mediated therapy resistance as an adaptive, nongenetic process driven by transcriptional and epigenetic reprogramming, metabolic flexibility, ECM stiffening–induced mechanotransduction, and immune‐checkpoint plasticity under therapeutic pressure. Together, these findings establish tumor plasticity and microenvironmental heterogeneity as an integrated, evolving system that fuels metastasis and limits durable treatment responses. Targeting this tumor–TME plasticity axis represents a promising strategy to disrupt metastatic progression and overcome therapeutic resistance.

Therapy resistance and disease recurrence remain major challenges across cancer types despite substantial advances in targeted therapy, chemotherapy, and immunotherapy. In many clinical settings, treatments successfully engage stress and death signaling pathways and produce rapid tumor regression, yet complete and durable eradication is uncommon. A consistent pattern emerges in which most tumor cells are eliminated while a small fraction survives, persists as residual disease, and later drives relapse. These observations suggest that failure is not always due to the absence of death pathways, but rather to incomplete execution. Here, we synthesize emerging evidence supporting the view that regulated cell death operates as a threshold-governed, highly plastic process. Apoptosis, ferroptosis, and inflammatory death programs remain largely intact in many tumors but are tightly controlled by buffering networks that regulate mitochondrial commitment, redox balance, metabolic state, and inflammatory signaling. Under therapeutic pressure, cancer cells frequently activate proximal death signaling without progressing to irreversible collapse. Sublethal engagement can generate stressed but viable cell states that contribute to drug tolerance, minimal residual disease, and later resistance evolution. Clinical data across hematologic and solid malignancies reinforce this framework. Biomarkers of pathway activation often correlate with early response but do not reliably predict long-term benefit. Dose limitations, treatment interruptions, and adaptive rewiring further allow surviving populations to recover and expand. We propose that execution depth, rather than pathway activation alone, represents a critical determinant of durable response. This perspective supports therapeutic strategies that simultaneously drive death signaling while disabling buffering systems, prevent adaptive state transitions, and incorporate immune-mediated clearance to achieve sustained tumor elimination.

Glutaminolysis, the metabolic process of converting glutamine into key intermediates, plays an essential role in cellular energy production, signaling, biosynthesis, and redox balance. Deregulation of glutamine metabolism significantly influences various pathological conditions, including cancers and metabolic and neurological diseases. Emerging evidence shows that long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and oncogenic alterations in glutamine transporters and enzymes enhance glutamine's role as an alternative energy source, supporting cell survival and proliferation under nutrient and oxygen deprivation conditions. To combat the pathogenic effects of altered glutamine metabolism, researchers are developing targeted inhibitors of key enzymes and transporters involved in glutaminolysis. By interfering with the mechanisms that support the growth of cancer cells, these inhibitors may be able to stop the growth of tumors and treat metabolic and neurological conditions. This review provides a comprehensive overview of existing inhibitors and ongoing clinical trials targeting glutamine metabolism, focusing on its potential as a cancer therapeutic strategy. Additionally, the role of lncRNAs and circRNAs in regulating glutamine metabolism is explored, revealing novel avenues for therapeutic intervention in cancer and other diseases.

The concept of tumors as prion-like diseases similar to neurodegenerative disorders has gained attraction in recent years. p53, the most well-known tumor suppressor, has been extensively studied for its expression, mutations, and functions in various cancers. Recent findings reveal that p53 undergoes prion-like aggregation in tumors, leading to pathological amyloid fibril formation, functional alterations, and tumor progression. The mechanisms of p53 aggregation involve mutations, structural domains, isoforms, and external factors such as Zn²+ concentrations, pH, temperature, and chaperone abnormalities. While the role of p53 aggregation in tumors is increasingly recognized, controversies remain regarding its precise pathogenic mechanisms. This chapter reviews the structural features of p53 amyloid fibrils, its aggregation characteristics and effects, and the molecular mechanisms driving this phenomenon. Additionally, this chapter summarizes current therapeutic approaches targeting p53 aggregation and prion-like behavior, including small molecules and peptides designed to inhibit aggregation and restore p53's tumor suppressive function. By illuminating these aspects, this chapter aims to deepen our comprehension of how p53 aggregation disrupts its physiological functions. It also highlights the potential of targeting these aggregates as a novel therapeutic strategy in cancer treatment.

Background: Type 1 diabetes (T1D) is strongly influenced by HLA variation, yet current genetic risk models developed largely in European cohorts perform suboptimally in Middle Eastern populations due to region specific allele frequencies, DR4 subtype heterogeneity, and distinct haplotype structures. We aimed to characterize HLA diversity in the Qatar Biobank (QBB) cohort and develop a Middle East optimized, machine learning based T1D risk model (MENA T1D-GRS). Methods: We analyzed high-coverage whole-genome sequencing data from >14,000 individuals comprising 7,359 healthy controls, and 410 clinically diagnosed T1D patients plus 230 first-degree relatives (FDR). High-resolution HLA typing was performed using HLA-LA, HLA-HD, and Kourami. Haplotype phasing, LD estimation, and association testing identified population-specific risk and protective configurations. We computed GRS2 using 66 genomic variants and trained an XGBoost classifier integrating 79 weighted HLA features and GRS2 components. Synthetic data augmentation (ADASYN) was applied to correct the class imbalance between T1D cases and controls, thereby enhancing model sensitivity. Model discrimination was evaluated by AUCROC. Results: The QBB cohort exhibited exceptional HLA diversity, with 305 DRB1-DQA1-DQB1 haplotypes. Established risk haplotypes, DR3-DQ2.5 and DR4-DQ8.1 were significantly enriched in T1D cases, with compound heterozygosity conferring >12-fold increased odds. Importantly, DRB1*04:03 was protective (OR=0.54), contrasting sharply with DRB1*04:02 and *04:05. GRS2 achieved an AUC of 0.74 vs. population controls and 0.65 vs. FDRs; AUC improved to 0.81 in autoantibody-positive cases. The MENA T1D-GRS model achieved AUC 0.79 (baseline) and 0.82 with ADASYN. Sensitivity improved to 75-80% in autoantibody-positive subgroups. SHAP analysis revealed allele-specific effects, highlighting the opposing roles of DR4 subtypes. Conclusion: The MENA T1D-GRS provides a population-tailored genomic risk prediction tool, outperforming existing scores and capturing non-linear HLA interactions. It supports early screening, differential diagnosis, and precision medicine efforts in Middle Eastern populations. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was supported by the JDRF grant 2-SRA-2022-1258-M-B and Internal Research Grant from Sidra Medicine - SDR400149. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee/IRB of Sidra Medicine and Qatar Biobank gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The QBB data used in this study is accessible upon application through the Qatar Biobank portal (https://www.qatarbiobank.org.qa/), pending institutional review board approval. Additional data produced in the present study are available upon reasonable request to the corresponding author

G protein-coupled receptors (GPCRs) are the largest and most diverse class of membrane proteins, mediating cellular responses to a wide range of extracellular stimuli. GPCRs initiate complex intracellular signaling networks that regulate vital physiological functions and are associated with numerous diseases, including various types of cancer. Their conserved seven-transmembrane (7TM) structure enables these signaling networks by allowing interactions with multiple ligands and intracellular effectors. In several types of tumors, abnormal GPCR signaling promotes carcinogenesis by supporting immune evasion, cell proliferation, and therapeutic resistance. A significant research gap exists in fully understanding the molecular mechanisms behind pathway-specific activation and biased ligand discovery of GPCRs, which could lead to the development of more effective therapies. This review examines the complexity of GPCRs, with a focus on their role in signaling through the differential activation of pathways regulated by β-arrestin and G proteins. It discusses how targeted modulation of signaling outcomes by receptor mutants might offer therapeutic benefits in cancer treatment. The review also highlights emerging technologies, such as aptamers, PROTACs, and nanobodies, that more precisely target GPCRs. In addition to exploring receptor structure-function relationships and pathway selectivity, this review provides valuable insights into GPCR-biased signaling and its implications in cancer biology.

Heat shock proteins (HSPs) are a conserved family of molecular chaperones that play a fundamental role in maintaining cellular homeostasis by facilitating protein folding, preventing aggregation, and mediating proteostasis under stress conditions. In cancer, HSPs are frequently overexpressed, contributing to tumor initiation, progression, metastasis, and therapeutic resistance. Their ability to stabilize oncoproteins, regulate apoptosis, and modulate immune responses makes them key players in tumorigenesis and promising therapeutic targets. This article comprehensively explores the classification and functional diversity of HSPs, highlighting their interactions with oncogenic pathways such as PI3K/AKT, MAPK, and p53. We discuss the dysregulation of prominent HSP families, including HSP27, HSP40, HSP60, HSP70, HSP90, and HSP110 across various cancer types, emphasizing their roles in promoting malignancy and modulating treatment responses. The chapter further elucidates how HSPs facilitate metabolic reprogramming in cancer cells, primarily through their interactions with key metabolic regulators, such as HIF-1α, c-Myc, and AKT, thereby sustaining the Warburg effect and promoting tumor cell survival. We examine their potential applications in precision oncology, including the development of HSP inhibitors, immunotherapies, and personalized treatment strategies. Additionally, we discuss novel therapeutic approaches, including chaperone-mediated autophagy modulation, HSP-based vaccines, and the integration of nanoparticle-mediated drug delivery systems. While HSP-targeted therapies offer significant promise, challenges such as drug resistance, toxicity, and compensatory upregulation of other chaperones remain formidable obstacles. Future research should focus on refining therapeutic selectivity, optimizing combination regimens, and utilizing advanced technologies, such as CRISPR-based gene editing and nanotechnology, to enhance treatment efficacy.

Breast cancer poses a significant clinical challenge due to its complex molecular landscape, underscoring the need for improved prognostic and therapeutic strategies. In this study, we explored the expression profiles and therapeutic relevance of circular RNAs (circRNAs) in a cohort of 96 breast cancer patients from Qatar representing the MENA region. Our data identified distinct expression patterns in relation to breast cancer subtypes, tumor grade, and age, with fifty circRNAs found to be associated with unfavorable relapse-free survival (RFS). The expression of sixteen of these circRNAs was validated in triple-negative breast cancer (TNBC) model using RNase R resistance assay. Among these, the expression of circ_0001522, circ_0001278, and circ_0001801 was validated using divergent primers, and their backsplice junctions were confirmed using Sanger sequencing. Functionally, siRNA-mediated knockdown of these circRNAs significantly suppressed cell proliferation, colony formation, three-dimensional organoid growth, and cell migration in TNBC models. Mechanistic investigations revealed that circRNA depletion altered a subset of miRNA and mRNA expressions, with key interactions involving miR-4458, miR-145-5p, and miR-760, regulating critical targets such as CCND1, ROBO4, and MMP1. Additionally, circRNA-RBP bioinformatic analysis identified common binding partners, including AGO2, CPSF7, TARDBP, UPF1, and LIN28B, suggesting roles in post-transcriptional regulation. Our data highlight circ_0001522, circ_0001278, and circ_0001801 as promising prognostic and therapeutic circRNA targets for breast cancer, offering new avenues for improving breast cancer prognosis and treatment.

BACKGROUND:Cervical cancer (CC) remains a major health burden in low- and middle-income countries, where HPV vaccination coverage is suboptimal. Ubiquitin-specific peptidase 14 (USP14), a proteasome-associated deubiquitinase, has emerged as a potential driver of tumorigenesis, but its role in CC and impact on tumor metabolism remain poorly defined. METHODS:In-silico analysis of RNA and proteomics data from publicly available datasets was performed to assess the expression and prognostic value of USP14. Expression was validated in CC cell lines (HeLa, SiHa, CaSki) in comparison to non-transformed MCF10A cells. Functional studies involved USP14 knockdown (siRNA) or inhibition (IU1), followed by various cell viability, metastasis and invasion assays. Comparative proteomics was employed to identify USP14 interacting partners, with a particular focus on monocarboxylate transporter 4 (MCT4). USP14-MCT4 interactions were confirmed by co-immunoprecipitation, ubiquitination assays, and molecular dynamics simulations. Immunohistochemistry was performed on retrospective cervical squamous cell carcinoma tissues to correlate USP14 and MCT4 expression. RESULTS:High USP14 expression correlated with poor overall survival in CC patients and was elevated in CC cell lines. Genetic or pharmacological inhibition of USP14 significantly reduced CC cell proliferation, metastasis, and invasion. Proteomic profiling identified MCT4, a key lactate transporter in tumor metabolism, as a novel USP14 interactor. USP14 knockdown decreased MCT4 protein levels and stability, suggesting deubiquitination-dependent regulation. Immunoprecipitation confirmed direct binding between USP14 and MCT4, and molecular dynamics simulations revealed distinct binding interfaces. In patient tissues, USP14 and MCT4 expression were positively correlated. CONCLUSION:This study uncovers MCT4 as a novel substrate of USP14, linking USP14 activity to metabolic reprogramming in CC. The USP14-MCT4 axis represents a previously unrecognized oncogenic pathway with therapeutic potential. Targeting USP14 could simultaneously impair tumor growth and disrupt lactate metabolism, offering a promising strategy for CC treatment.

Human papillomavirus (HPV) is a key driver of head and neck squamous cell carcinoma (HNSCC) and cervical squamous cell carcinoma (CESC). Yet, these cancers exhibit distinct molecular and clinical features influenced by HPV status. This study utilizes RNA sequencing data from The Cancer Genome Atlas (TCGA). It employs bioinformatics tools, including DESeq2 for differential gene expression, CIBERSORT for immune profiling, and Kaplan-Meier survival analysis to investigate these differences. Differential expression analysis revealed distinct molecular signatures, with HPV-positive tumors enriched in immune-related pathways such as cytokine-cytokine receptor interactions. In contrast, HPV-negative tumors exhibited upregulation of metabolic pathways, including PPAR signaling. Metaflux analysis further demonstrated contrasting metabolic profiles: HPV-positive tumors showed increased glycolysis and oxidative stress regulation, whereas HPV-negative tumors were characterized by elevated amino acid and nucleotide metabolism. Immune profiling highlighted more significant CD8 + T-cell infiltration in HPV-positive tumors, while HPV-negative tumors were predominantly associated with macrophages, suggesting differing tumor immune environments. Survival analysis identified CXCL11 and STAT1 as potential prognostic biomarkers, with lower expression correlating with poorer survival in both cancers. These findings provide an integrated perspective on the molecular, metabolic, and immune differences associated with HPV status, offering insights into potential therapeutic strategies.

Ritscher-Schinzel syndrome (RSS) is a congenital malformation syndrome characterized by cerebellar, cardiac, and craniofacial malformations and phenotypes associated with liver, skeletal, and kidney dysfunction. The genetic cause of RSS remains to be fully defined, and limited information is available regarding the root cause of the multiple tissue phenotypes. Causative mutations in the Commander multiprotein assembly are an emerging feature of this syndrome. Commander organizes the sorting nexin-17 (SNX17)-dependent recycling of hundreds of integral membrane proteins through the endosomal network. Here, we identify previously unrecognized cohorts of patients with RSS that we genetically and clinically analyzed to identify causative genes in the copper metabolic murr1 domain-containing (COMMD) proteins COMMD4, COMMD9, and coiled-coil domain containing 93 (CCDC93) subunits of the Commander complex. Using interactome analysis, we determined that these mutations disrupted Commander assembly and, through cell surface proteomics, that this reduces tissue-specific presentation of cell surface integral membrane proteins essential for kidney, bone, and brain development. We established that these integral proteins contained ΦxNPxY/F or ΦxNxxY/F sorting motifs in their cytoplasmic-facing domains (where Φ is a hydrophobic residue and x is any residue) that are recognized by SNX17 to drive their Commander-dependent endosomal recycling. Last, through generation of mouse models of RSS, we show replication of RSS-associated clinical phenotypes including proteinuria, skeletal malformation, and neurological impairment. Our data establish RSS as a "recyclinopathy" that arises from a dysfunction in the Commander endosomal recycling pathway.

Liquid biopsies, which analyze circulating tumor cells or cell-free circulating tumor DNA (ctDNA) from blood, have emerged as promising cancer detection and monitoring tools. Specifically, human papillomavirus (HPV) cell-free (cf) DNA is gaining recognition as a prognostic marker in high-risk HPV-related cancers. However, detecting circulating markers for cervical cancer (CC) requires highly sensitive techniques to quantify circulating HPV DNA. This study aimed to evaluate the use of droplet digital PCR (ddPCR), a highly sensitive technique, for detecting and quantifying circulating HPV DNA in cervical cancer patients, both at baseline (before chemo- or radiotherapy) and during follow-up, to assess its utility as a prognostic marker. Blood samples were collected from 60 cervical cancer patients (Stages I-IV) at AIIMS, New Delhi, at baseline and three months post-treatment. Samples from 10 healthy controls were also included. Plasma was separated and stored at - 80 °C, and cfDNA was extracted from 1 ml of plasma. The presence of high-risk HPV types, HPV16 and HPV18, in cfDNA from 35 patients was assessed using ddPCR. The median concentration of cfDNA in cervical cancer patients was 9.35 ng/µL at baseline, which decreased to 7 ng/µL after three months of treatment. In healthy controls, the median cfDNA concentration was 6.95 ng/µL. ddPCR screening showed that detection rates for HPV18 and HPV16 detection were 45.71% and 82.86%, respectively. A significant correlation was observed between cf HPV16 DNA levels and tumor size, suggesting its potential as biomarker for disease burden.

Prostate cancer (PC) is one of the second most common cancer diagnosed and the second most common cause of cancer death in men worldwide. Currently combinations of tumor surveillance, surgery, radiation, hormonal, and chemotherapies are used in the management and treatment of prostate cancer. The molecular basis of disease is complex and mutations in many different oncogenes and tumor suppressor genes have been found including TP53, RB1, EZH2, BMI, and PTEN. The oncogenesis of prostate cancer appears to be caused by dysregulation of many different cellular signalling pathways especially those involved in cell survival and apoptosis. Protein deubiquitination controls many intracellular processes, including cell cycle progression, transcriptional activation, and signal transduction. Ubiquitin specific peptidases (USPs) remove ubiquitin tags from target proteins to alter protein configuration and function. Recent studies have revealed that Ubiquitin specific peptidase 37 (UPS37) regulates replication stress by regulating important protein involved in several important cellular functions. Analysis of TCGA data indicated that overexpression of USP37 correlated with reduced progression free survival (PFS) in prostate cancer patients. Mass spectrometery analysis of Prostate cancer cells (DU145) indicated that distinct set of genes were altered on overexpression or knockdown of USP37. Our data indicate that USP37 overexpression confers survival advantage while its depletion enhances sensitivity for cell killing in PC cells. USP37 overexpressing cells were able to resolve DNA damage foci much more rapidly than the control cells or cells in which USP37 was depleted in response to genotoxic stress. USP37 depletion results in reduced resolution of γ H2AX and 53BP1 DNA damage foci which indicates the reduced ability of cells to carry out constitutive DNA replication. USP37 was found to interact with different replication factors as also seen in our mass spectrum analysis. We further correlated our data with archived tissue blocks of PC patients by analysing if USP37 overexpression correlated with disease progression. Present data suggests that USP37 is required for tolerance of replication stress in PC and is required to dock additional replication factors and stabilize DNA replication fork. The current data provides new mechanistic details for the regulation of replication stress by USP37 which merits the development of targeting strategies to explore its therapeutic potential in PC by inducing synthetic lethality. Gunjan Dagar, Asha Khuswaha, Lakshay Malhotra, Ashna Gupta, Ajaz Bhat, Ammira S Al-Shabeeb Akil, Atul Batra, Seema Khausal, Mayank Singh. Ubiquitin specific peptidase 37 facilitate prostate cancer oncogenesis by regulation replication stress [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1429.

COP1 and DET1 are components of an E3 ubiquitin ligase that is conserved from plants to humans. Mammalian COP1 binds to DET1 and is a substrate adaptor for the CUL4A-DDB1-RBX1 RING E3 ligase. Transcription factor substrates, including c-Jun, ETV4, and ETV5, are targeted for proteasomal degradation to effect rapid transcriptional changes in response to cues such as growth factor deprivation. Here, we link a homozygous DET1R26W mutation to lethal developmental abnormalities in humans. Experimental cryo-electron microscopy of the DET1 complex with DDB1 and DDA1, as well as co-immunoprecipitation experiments, revealed that DET1R26W impairs binding to DDB1, thereby compromising E3 ligase function. Accordingly, human-induced pluripotent stem cells homozygous for DET1R26W expressed ETV4 and ETV5 highly, and exhibited defective mitochondrial homeostasis and aberrant caspase-dependent cell death when differentiated into neurons. Neuronal cell death was increased further in the presence of Det1-deficient microglia as compared to WT microglia, indicating that the deleterious effects of the DET1 p.R26W mutation may stem from the dysregulation of multiple cell types. Mice lacking Det1 died during embryogenesis, while Det1 deletion just in neural stem cells elicited hydrocephalus, cerebellar dysplasia, and neonatal lethality. Our findings highlight an important role for DET1 in the neurological development of mice and humans.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy characterized by the aberrant activation of survival pathways, particularly the PI3K/AKT axis. Pristimerin (Prist), a naturally occurring quinonemethide triterpenoid, has recently gained attention for its anti-cancer potential. In this study, we demonstrate that Prist effectively inhibits the proliferation of T-ALL cell lines (Jurkat and Molt 4) by inducing G0/G1 cell cycle arrest and triggering intrinsic and extrinsic caspase-dependent apoptosis. Prist significantly increases reactive oxygen species (ROS) levels and depletes glutathione (GSH), leading to mitochondrial dysfunction and cytochrome c release. Notably, ROS scavenging with N-acetylcysteine (NAC) abrogated Prist-induced apoptosis, highlighting ROS as a critical mediator of its cytotoxicity. Network pharmacology and molecular docking revealed AKT as a key target of Prist, with strong binding affinity confirmed through docking analysis. Prist downregulated phosphorylated AKT and inhibitor of apoptosis proteins (XIAP, cIAP1/2), supporting its pro-apoptotic mechanism. Importantly, Prist inhibited the proliferation and AKT phosphorylation in activated primary human T cells but spared resting T cells, indicating selective cytotoxicity. These findings establish Prist as a promising therapeutic candidate for T-ALL through the selective targeting of PI3K/AKT-driven survival signaling.

Background and Clinical Significance: Methyltransferase-like protein 5 (METTL5) is a conserved RNA methyltransferase responsible for catalyzing the N6-methyladenosine (m6A) modification of 18S ribosomal RNA, a process critical for ribosome biogenesis and translational regulation. Biallelic variants in METTL5 have been linked to autosomal recessive intellectual developmental disorder-72 (MRT72), typically presenting with microcephaly, intellectual disability, and speech delay. However, the association between METTL5 and isolated attention-deficit/hyperactivity disorder (ADHD) remains underexplored. Case Presentation: We report a 14-year-old Qatari female, born to consanguineous parents, who presented with microcephaly, speech delay, learning difficulties, and inattentive-type ADHD. Trio-based whole-genome sequencing identified a novel homozygous METTL5 variant (c.617G > A; p. Arg206Gln), with both parent’s heterozygous carriers. The variant is extremely rare (gnomAD MAF: 0.0000175) and predicted to be deleterious (CADD: 23.7; SIFT: damaging; PolyPhen-2: probably damaging). Structural modeling localized the change within the SAM-dependent catalytic domain, predicting protein destabilization (ΔΔG = +1.8 kcal/mol). The affected residue is highly conserved (ConSurf score: 8), and protein–protein interaction analysis linked METTL5 with METTL14, METTL16, and ZCCHC4, key regulators of rRNA methylation. Conclusions: In silico evidence suggests that the p. Arg206Gln variant disrupts METTL5 function, likely contributing to the observed neurodevelopmental phenotype, including ADHD. This expands the clinical spectrum of METTL5-related disorders and supports its inclusion in neurodevelopmental gene panels.

Proteomics has become a transformative tool in oncology, offering unique opportunities for early detection, diagnosis, and cancer stratification. By enabling large-scale analysis of protein expression, interactions, and post-translational modifications, proteomics facilitates the discovery of clinically relevant biomarkers that reflect the dynamic molecular state of disease. These biomarkers, often detectable in easily accessible body fluids like blood, urine, or saliva, serve as minimally invasive “liquid biopsies” capable of identifying malignancies at asymptomatic stages. The integration of high-resolution mass spectrometry with advanced computational methods, including machine learning and network-based analytics, has accelerated the identification of reliable biomarker panels for cancer prediction, monitoring, and treatment response. Proteomics not only complements genomic and transcriptomic data but also provides a functional view of cellular states, bridging the gap between genotype and phenotype. This is especially important for customizing personalized treatment plans based on tumor-specific protein profiles, thus reducing the off-target effects of traditional therapies. Furthermore, proteomics plays a crucial role in finding cancer-related mechanisms, such as immune evasion, angiogenesis, and metastatic progression. Although proteomics-based biomarker discovery holds critical promise for cancer diagnosis and precision medicine, substantial translational challenges remain. These include assay standardization, sample accessibility from a regional biobank, regulatory obstacles, cross-population validation, and the integration of discoveries into clinical workflows. In this perspective, we offer a comprehensive overview of the latest progress in proteomics-driven cancer biomarker discovery, with a particular focus on its translational potential in early detection and precision oncology. The increasing incidence of cancer in the Middle East is highlighted, necessitating an urgent expansion of research into population-specific biomarkers.